Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium

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1 Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium Cathelijne H. van der Wouden, PharmD PhD Candidate U-PGx Dept. of Clinical Pharmacy &Toxicology

2 Pharmacogenomics in precision medicine PGx Promise: Personalize medicine by using an individual's genetic makeup to predict drug response to guide optimal drug and dose selection Achieved by pre-emptive pharmacogenomic testing

3 Current Evidence Supporting Pre-emptive Pharmacogenomics Gold standard evidence for a variety of single drug-gene pairs: Drug Clinical Endpoint Variant Abacavir hypersensitivity HLA-B*5701 Acenocoumarol / Fenprocoumon % time between therapeutic INR VKORC1/CYP2C9 Warfarin % time between therapeutic INR VKORC1/CYP2C9 Warfarin % time between therapeutic INR VKORC1/CYP2C9 Mercaptopurine leucopenia TPMT Sufficient evidence supporting that pre-emptive PGx can lead to improved patient outcome Evidence base is limited to single druggene pairs

4 PGx Testing for a Panel of Pharmacogenes is More Relevant PGx results are lifelong Patients may initiate a number of drugs during their life time which can be more optimally prescribed using PGx Actionable PGx variants are common in the population 100% 80% 60% 40% 20% 0% Evidence supporting a panel approach is currently undetermined CYP2C19 CYP2C9 CYP2D6 CYP3A5 DPYD HLA-B SLCO1B1 TPMT UGT1A1 VKORC1 95% of patients have at least 1 actionable genotype Dunnenberger, Annu Rev Pharmacol Toxicol 2015

5 U-PGx Consortium: Generating Evidence to Support Pharmacogenomics Objective: to quantify the collective clinical utility of a panel of PGx-markers 1. Systematic implementation of pre-emptive PGx strategy across multiple: drugs/genes/ethnicities/healthcare systems 2. Robust assessment of how this intervention impacts: Patient care (individual and on a population level) Healthcare service processes Cost-effectiveness

6 Ubiquitous Pharmacogenomics Funded by EU Horizon 2020 ( 15 million) Start year project Implement pre-emptive PGx testing in a real world setting across 7 European sites Using the DPWG guidelines to guide drug and dose selection

7 U-PGx Consortium PREPARE STUDY COMPONENT III COMPONENT II N=8,100 COMPONENT I COMPONENT IV

8 Component 2: PREPARE Study Co-ordinating Principal Investigator: Dr. Jesse Swen Objective: To quantify the collective clinical utility of a panel of PGx-markers covering 13 important pharmacogenes as a new model of personalized medicine Hypothesis: Implementation will result in a 30% reduction of clinically relevant adverse drug reactions (4 2.8%) Design: Open randomized cross-over study in 7 countries including 8,100 patients. Outcomes: Primary Secondary Clinical outcome Process indicators for implementation Cost-effectiveness

9 PREPARE PREemptive Pharmacogenomic testing for preventing Adverse drug REactions New set of patients Spain, Greece, Slovenia N=4,050 N=4,050 Netherlands, UK, Austria, Italy Each site has its own therapeutic focus

10 PGx Guided Prescribing Arm T=2, 4, 8, 12 weeks 1 st Rx PGx drug DNA sample Record in EMR PGx informed prescribing Safety code card provided

11 Drugs of inclusion (n=42) Antiarrhythmic Flecainide Propafenon Analgesic Codeine Oxycodone Tramadol Anticancer Capecitabine Fluorouracil Irinotecan Tamoxifen Tegafur Anticoagulant Acenocoumarol Clopidrogel Phenprocoumon Warfarin Antidepressant Citalopram Escitalopram Paroxetine Sertraline Venlafaxine Antidepressant (TCA) Amitriptyline Clomipramine Doxepine Imipramine Nortryptiline Antiepileptic Carbamazepine Phenytoin Antihypertensive Metoprolol Anti-infective Efavirenz Flucloxacillin Voriconazole Antipsychotic Aripiprazole Clozapine Haloperidol Pimozide Zuclopenthixol Cholesterol-lowering Atorvastatin Simvastatin Immunosuppressant Azathioprine Mercaptopurine Tacrolimus Thioguanine Psychostimulant Atomoxetine PPIs excluded because they are only associated with a difference in efficacy among aberrant genotypes Estrogen containing drugs will only be included in the study as a subsequent prescription.

12 Standard of Care Arm T=2, 4, 8, 12 weeks 1 st Rx PGx drug DNA sample Standard prescribing Mock Safety code card provided

13 Subsequent Prescriptions of Interest T=2, 4, 8, 12 weeks T=2, 4, 8, 12 weeks T=2, 4, 8, 12 weeks 1 st Rx PGx drug DNA Sample Record in EMR PGx informed prescribing 2 nd Rx PGx drug 3 rd Rx PGx drug ~50% 2 nd prescription ~30% 3 rd prescription

14 Primary Composite Endpoint

15 Example: Composite Endpoint Patient in standard of care arm Drug of inclusion: Codeine, normal dose Adverse drug reaction: Respiratory depression Severity: CTCAE Grade 5 Causality: LCAT Possible Genotype: CYP2D6 Ultra Rapid Metabolizer Drug genotype association: Described in the underlying literature of the codeine DPWG guideline to be associated with CYP2D6 UM

16 Secondary Endpoints Secondary analyses of the U-PGx project are aimed at evaluating quantitative and qualitative indicators for successful implementation strategies. Composite endpoint for all prescriptions Cost-effectiveness (incl QOL using the EQ5D questionnaire) Secondary clinical outcome measures Drug cessation (due to lack of efficacy, due to an ADR) Dose alteration Additional drugs prescribed Survey of patients and physicians regarding: multi-domains (e.g. beliefs, knowledge, usability) process indicators for implementation (e.g. guideline compliance, extent of adoption, number of tests) among patients and physicians Patient reported outcomes (PROs) Routine drug levels Health-care consumption

17 PREPARE: Data Collection 1. ecrf: ProMISe Research Nurse Follow-up Baseline (± 1 week)* 4 weeks (± 1 week) * 12 weeks (± 1 week)* End of Study (± 4 weeks) 2 nd Rx 50%, 3 rd Rx 30% *For every newly prescribed drug of interest 2. LIM Online Survey Follow-up 2 weeks* 8 weeks* *For every newly prescribed drug of interest

18 Primary Statistical Analysis Logistic regression analysis: Number of patients who experience at least one ADR contributing to the primary composite endpoint in the study arm vs control arm Gatekeeping analysis: 1. Among patients with an actionable druggenotype interaction 2. Among all patients included in the study

19 1. Received a Recommendation vs Did Not Receive Recommendation Control arm N=4,050 Study arm N=4,050 Actionable drug-gene interaction Estimated 30% of N Wild-type Actionable drug-gene interaction Estimated 30% of N Wild-type Normal dose (standard of care) Reduced starting dose Alternative drug selected Normal dose (standard of care) % Grade 2 toxicity %Grade 2 toxicity % Grade 2 toxicity % Grade 2 toxicity Step 1 comparison

20 2. Among All Patients Included Control arm N=4,050 Study arm N=4,050 Actionable drug-gene interaction Estimated 30% of N Wild-type Actionable drug-gene interaction Estimated 30% of N Wild-type Normal dose (standard of care) Reduced starting dose Alternative drug selected Normal dose (standard of care) % Grade 2 toxicity % Grade 2 toxicity % Grade 2 toxicity % Grade 2 toxicity ~4% ~2.8% Step 2 comparison

21 Component 3: A next step into the Future Leader: Prof. Dr. Matthias Schwab Follow-up study among extreme phenotypes: Next Generation Sequencing To identify rare variants Blood sample within 24 hours of serious ADR Blood plasma levels of drugs Rare variants among CYPs Pharmacokinetic sub-study: Integrate Gene-Drug and Drug-Drug interactions Apply a systems pharmacology approach Dried blood spot at various time points combined with clinical endpoint data Wist Genome Medicine2009;1:11 1. Ingelman-Sundberg, Genetics in Medicine 2016

22 Future perspective and collaboration Routine PGx guided prescribing will become a reality in the EU in the near future PREPARE Study will quantify collective clinical utility of a panel of PGx-markers PREPARE is unique in its multi-center, multi-gene, multi-drug, multiethnic, and multi-healthcare system approach PREPARE will deliver a large dataset combining detailed phenotypes of adverse drug reactions and individuals genetic makeup U-PGx is open for collaboration to expand understanding of PGx

23 U-PGx Consortium H.J. Guchelaar (Coordinator), J.J. Swen, M. Kriek M. Pirmohamed, R. Turner J. Stingl M. Ingelman-Sundberg C. Mitropoulou M. van Rhenen, K.C. Cheung D. Steinberger V.H.M. Deneer M. Samwald G. Sunder-Plassmann A. Cambon-Thomsen M. Karlsson S. Jo nsson G. Toffoli E. Cecchin C.L. Davila Fajardo G. Patrinos V. Dolz an M. Schwab E. Schaeffeler

24 Thank you for your attention! U-PGx Kick-off Leiden Jan 19 th, This project has received funding from the European Union s Horizon 2020 research and innovation programme under grant agreement No